Business Context

RideNow is a two-sided rideshare app expanding in 12 U.S. cities. Over the last month, rider acquisition spend increased, but first-ride conversion has stalled, so the Growth PM wants to identify the biggest opportunity in the rider onboarding flow.

Metric Scenario

In April, 500,000 new users installed the app and started onboarding. The current rider onboarding funnel is:

1. App install: 500,000 users
2. Account created: 410,000 users
3. Phone verified: 360,000 users
4. Payment method added: 250,000 users
5. Pickup/dropoff entered: 180,000 users
6. Ride requested: 150,000 users
7. First ride completed: 120,000 users

Leadership wants to know where the largest opportunity is: the step with the biggest absolute drop, the lowest step conversion, or the step with the highest expected impact on completed first rides if improved. They also want to know whether the answer changes by platform, city, and acquisition channel.

Requirements

1. Define the primary onboarding funnel metric and the supporting step-level metrics you would use.
2. Use the funnel data above to identify the biggest opportunity in the onboarding flow and explain your reasoning.
3. Show how you would distinguish between absolute drop-off, relative conversion rate, and downstream impact.
4. Describe how you would segment the funnel to avoid misleading conclusions.
5. Propose 3 specific product hypotheses for the weakest step and how you would validate them.

Data Available

• app_installs: install timestamp, user_id, platform, campaign_id, city
• onboarding_events: account_created, phone_verified, payment_added, address_entered, ride_requested timestamps
• rides: ride_id, user_id, request_time, completion_time, city, cancellation_reason
• payments: user_id, card_type, add_payment_success, failure_reason
• user_profile: user_id, signup_date, referral_code, device_type, country